Scientific workflows are increasingly used to rapidly integrate existing algorithms to create larger and more complex programs. However, designing workflows using purely dataflow-oriented computation models introduces a number of challenges, including the need to use low-level components to mediate and transform data (so-called shims) and large numbers of additional “wires” for routing data to components within a workflow. To address these problems, we employ Virtual Data Assembly Lines (VDAL), a modeling paradigm that can eliminate most shims and reduce wiring complexity. We show how a VDAL design can be implemented using existing XML technologies and how static analysis can provide significant help to scientists during workflow design and evolution, e.g., by displaying actor dependencies or by detecting so-called unproductive actors.